The present application is related generally to methods for calibrating a machine vision vehicle measurement system, and in particular, to methods for establishing distance scale factors or calibration parameters associated with individual optical targets of a machine vision vehicle measurement system to improve the accuracy of acquired vehicle measurements, such as vehicle symmetry measurements.
Vehicle symmetry measurements are based on the relative positions of a vehicle's four wheels, and include quantities such as wheelbase, setback, lateral offset, etc. Traditionally, vehicle symmetry measurements determined by a machine vision vehicle measurement or wheel alignment system are computed based on an assumption that a set of wheel-mounted optical targets which are observed by the imaging sensors of the machine vision system have been constructed to precise design dimensions, and have not undergone significant changes in size and shape over time. However, it has been observed that even small variations in the size and shape of features on the machine vision targets can introduce biases in the symmetry measurements. For example, if a left rear optical target and a right rear optical target in a machine vision system differ in size by one tenth of a percent or more, inter-camera transforms determined through a conventional optimization and calibration procedure may suffer significant distortion.
Current target characterization procedures used with commercially available machine vision vehicle wheel alignment systems, such as those sold by Hunter Engineering Co. of St. Louis, Mo. produce a model of the machine vision optical targets represented as scaled variations from the particular optical target's ideal design. Such machine vision vehicle service system imaging sensors or cameras introduce a bias when measuring a distance to a machine vision optical target disposed within a field of view if the calibrated focal length stored with the imaging sensor or camera calibration parameters deviates from the effective focal length. Such imaging sensor or camera-based bias is considered a minor defect in the process of calibrating a machine vision imaging sensor or camera, and is expected. It is a system design decision whether to seek to provide some after-the-fact correction of any measurement bias that results from such imperfection.
A precision distance calibration procedure for use with a machine vision vehicle inspection or wheel alignment system would be advantageous in order to accurately account for deviations in the system between ideal configurations and actual configurations of components. Accounting for deviations such as actual spacing between optical target elements or imaging sensor focal lengths could provide improved distance measurements and enable an overall improvement in measurement accuracy for the machine vision vehicle service or inspection system.